Senior ML Engineer Jobs in Texas
Senior ML Engineer jobs in Texas are among the most active in the country, concentrated in technology, financial services, energy, and defense sectors with demand at every level from mid-career practitioner through principal and staff engineer. Austin, Dallas, and Houston lead hiring volume, with employers like Dell Technologies, JPMorgan Chase, and ExxonMobil maintaining deep, sustained ML engineering teams across the state. The most in-demand specializations are large language model deployment, MLOps and model infrastructure, and computer vision applied to industrial and energy systems. Find a role that fits below and apply directly.
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INTRODUCTION
What we're doing isn't easy, but nothing worth doing ever is.
We envision a future powered by robots that work seamlessly with human teams. We build artificial intelligence that enables service robots to collaborate with people and adapt to dynamic human environments. Join our mission-driven team as we build out current and future generations of robots.
ROLE AND RESPONSIBILITIES
As a Sr. ML Engineer, Autonomous Navigation, you will develop learning-based navigation models that enable Moxi to move naturally and safely around people, beds, wheelchairs, and equipment. You'll train policies using fleet data (imitation learning) and refine behavior with simulation and RL. Your work will directly impact delivery speed, reduced hesitation/deadlocks, and fewer interventions in real hospital deployments.
- Develop learning-based navigation models that predict safe, smooth trajectories from sensor inputs and/or perception representations.
- Build imitation learning pipelines from fleet logs (trajectory extraction, filtering, scenario balancing, evaluation).
- Implement simulation-based refinement (RL, reward shaping, domain randomization) to improve robustness.
- Define navigation success metrics aligned to product outcomes.
- Collaborate with the AI Platform team to integrate learned policies behavior/safety systems and validate on-robot.
- Build regression tests and scenario replay suites for challenging scenarios.
- Analyze field behavior, identify failure modes, and close the loop through data curation and retraining.
BASIC QUALIFICATIONS
- Bachelor's or Master's degree in Robotics, Computer Science, Electrical Engineering, or related field (PhD a plus).
- 5+ years of experience in ML for robotics and/or autonomous vehicles.
- Experience with Vision-Language-Action (VLA) models, behavior cloning, and/or transformer/diffusion policies for robotic control.
- Strong proficiency in PyTorch and experience with sequence models / policy learning.
- Experience with imitation learning and/or reinforcement learning in robotics or autonomy contexts.
PREFERRED QUALIFICATIONS
- Experience with socially-aware navigation, dynamic obstacle avoidance.
- Experience with RL at scale (simulation rollouts, distributed training, stability/debugging).
- Familiarity with ROS navigation stacks and safety constraints for mobile robots.
- Experience building eval harnesses (offline replay, scenario libraries).
INTRODUCTION
What we're doing isn't easy, but nothing worth doing ever is.
We envision a future powered by robots that work seamlessly with human teams. We build artificial intelligence that enables service robots to collaborate with people and adapt to dynamic human environments. Join our mission-driven team as we build out current and future generations of robots.
ROLE AND RESPONSIBILITIES
As a Sr. ML Engineer, Autonomous Navigation, you will develop learning-based navigation models that enable Moxi to move naturally and safely around people, beds, wheelchairs, and equipment. You'll train policies using fleet data (imitation learning) and refine behavior with simulation and RL. Your work will directly impact delivery speed, reduced hesitation/deadlocks, and fewer interventions in real hospital deployments.
- Develop learning-based navigation models that predict safe, smooth trajectories from sensor inputs and/or perception representations.
- Build imitation learning pipelines from fleet logs (trajectory extraction, filtering, scenario balancing, evaluation).
- Implement simulation-based refinement (RL, reward shaping, domain randomization) to improve robustness.
- Define navigation success metrics aligned to product outcomes.
- Collaborate with the AI Platform team to integrate learned policies behavior/safety systems and validate on-robot.
- Build regression tests and scenario replay suites for challenging scenarios.
- Analyze field behavior, identify failure modes, and close the loop through data curation and retraining.
BASIC QUALIFICATIONS
- Bachelor's or Master's degree in Robotics, Computer Science, Electrical Engineering, or related field (PhD a plus).
- 5+ years of experience in ML for robotics and/or autonomous vehicles.
- Experience with Vision-Language-Action (VLA) models, behavior cloning, and/or transformer/diffusion policies for robotic control.
- Strong proficiency in PyTorch and experience with sequence models / policy learning.
- Experience with imitation learning and/or reinforcement learning in robotics or autonomy contexts.
PREFERRED QUALIFICATIONS
- Experience with socially-aware navigation, dynamic obstacle avoidance.
- Experience with RL at scale (simulation rollouts, distributed training, stability/debugging).
- Familiarity with ROS navigation stacks and safety constraints for mobile robots.
- Experience building eval harnesses (offline replay, scenario libraries).
See All 70 Senior ML Engineer Jobs in Texas
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Find Senior ML Engineer JobsSenior ML Engineer Jobs by City in Texas
Where Texas roles are concentrated, by current openings.
Senior ML Engineer Job Market in Texas
A snapshot from current Texas openings, updated as new roles post.
Who's Hiring
- Apple9
- Vitol5
- NVIDIA4
- PepsiCo4
- Amazon Web Services3
Top Industries Hiring
- Technology & Software23
- Banking & Financial Services10
- Electronics & Hardware9
- Energy4
- Food & Beverage4
What Texas Employers Look For
The qualifications that appear most often in senior ML engineer jobs across Texas.
- Bachelor's or master's degree in computer science, statistics, or a related quantitative field
- Five or more years of experience building and deploying production machine learning models
- Proficiency in Python and core ML frameworks such as TensorFlow, PyTorch, or scikit-learn
- Demonstrated experience with MLOps tooling, model monitoring, and CI/CD pipelines for ML
- Hands-on work with cloud platforms, particularly AWS SageMaker, Google Vertex AI, or Azure ML
- Strong communication skills for translating model performance and tradeoffs to non-technical stakeholders
Senior ML Engineer Jobs in Texas: Frequently Asked Questions
How do you become a senior ml engineer in Texas?
Senior ML engineer roles in Texas require no state-issued license or registration, so the path runs through education and demonstrated production experience. Most Texas employers expect a bachelor's or master's degree in computer science, applied mathematics, or a related field, combined with several years of end-to-end ML work. Building a portfolio of deployed models, contributing to open-source projects, and earning cloud certifications from AWS or Google Cloud strengthens a candidacy in a competitive Texas market.
How much do senior ML engineers make in Texas?
Senior ML engineers in Texas earn a median of about $111,530 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $55,480 for the lowest 10% to over $174,300 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire senior ml engineers in Texas?
Employers hiring senior ml engineers in Texas right now include Apple, Vitol, and NVIDIA, based on current listings on Migrate Mate as of June 2026. Texas's mix of Fortune 500 headquarters, major financial institutions, and large energy companies creates sustained, year-round ML engineering demand that extends well beyond the Austin tech corridor.
Which Texas cities have the most senior ml engineer jobs?
Austin, Dallas, and Houston hold the most senior ml engineer openings in Texas. Austin drives volume through its dense concentration of technology companies and semiconductor firms, Dallas pulls demand from financial services and large corporate headquarters, and Houston's energy and healthcare industries generate strong ML hiring tied to industrial automation, predictive maintenance, and clinical analytics.
Are there remote senior ml engineer jobs in Texas?
Yes, and more than most fields. About 21% of senior ml engineer openings tied to Texas are remote or hybrid as of June 2026, reflecting the desk-based, collaborative-tool-friendly nature of ML development work. Model research, experimentation, and pipeline engineering translate well to remote settings, while roles involving on-site hardware, robotics, or real-time sensor systems more commonly require an in-person presence.
How can I get hired as a senior ml engineer in Texas with little or no experience?
The most realistic entry path is transitioning from a data analyst, data scientist, or software engineering role into ML work through internal project exposure or adjacent hiring. Large Texas employers such as Dell, AT&T, and major Houston energy firms run new-graduate rotational and associate data science programs that feed into ML teams. Building a portfolio of end-to-end projects on public datasets, earning a cloud ML certification, and targeting associate ML engineer or ML platform engineer titles positions a candidate for the jump into senior work within a few years.
Where can I find and apply to senior ml engineer jobs in Texas?
You can find and apply to senior ml engineer jobs in Texas on Migrate Mate, which lists current Texas openings across industries and metros. Find roles that fit your background and apply directly from the listings on this page.
See All 70 Senior ML Engineer Jobs in Texas
Find roles in Texas that match your experience and apply in just a few clicks.
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